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Motility-induced phase separation enables swarm aggregation to be regulated without prescribing a target spatial distribution. This paper develops a partial differential equation-constrained model predictive control framework for a vibration-driven robotic swarm. Three continuum models retaining progressively less orientation information are considered to study the trade-offs among model fidelity, information requirements, and computational cost. The framework is evaluated under centralized and decentralized settings, with focus on how limited sensing and local-to-global phase-separation estimation affect the performance of predictive control.

生成讲解博客的中文版本

生成AI智能校验的中文版本